• DocumentCode
    30973
  • Title

    Evolutional algorithm based cascade long reach passive optical networks planning

  • Author

    Gu Rentao ; Liu Xiaoxu ; Li Hui ; Bai Lin

  • Author_Institution
    State Key Lab. of Inf. Photonics & Opt. Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
  • Volume
    10
  • Issue
    4
  • fYear
    2013
  • fDate
    Apr-13
  • Firstpage
    59
  • Lastpage
    69
  • Abstract
    In this paper, we propose a mathematical model for long reach Passive Optical Networks (PON) planning. The model considers the traffic demand, user requirements and physical constraints. It can support conventional star-like topologies as well as cascade PON networks. Then a two-stage evolutional algorithm is described to solve this problem. The first stage was to find a proper splitter candidate site set, composing the outer loop. The second stage aimed to get the optimal topology when the splitter locations were selected, composing the internal loop. In this algorithm, the Prüfer sequence is used to build up a one-to-one correspondence between a PON network configuration and a chromosome. Compared with the results obtained by the enumeration method, the proposed model and algorithm are shown to be effective and accurate.
  • Keywords
    evolutionary computation; mathematical analysis; passive optical networks; telecommunication network planning; telecommunication network topology; telecommunication traffic; PON networks; cascade long reach passive optical networks planning; evolutional algorithm; mathematical model; physical constraints; star-like topologies; traffic demand; user requirements; Evolutionary computation; Network topology; Optical fiber cables; Optical network units; Passive optical networks; Planning; Telecommunication network management; Prüfer sequence; evolutional algorithm; network planning; passive optical networks;
  • fLanguage
    English
  • Journal_Title
    Communications, China
  • Publisher
    ieee
  • ISSN
    1673-5447
  • Type

    jour

  • DOI
    10.1109/CC.2013.6506931
  • Filename
    6506931